東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Machine learning and knowledge disco...

ECML PKDD (Conference) ((2020 :)

FindBook

Google Book

Amazon

博客來

Machine learning and knowledge discovery in databases = European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.. Part V /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning and knowledge discovery in databases/ edited by Frank Hutter ... [et al.].
其他題名:	European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.
其他題名:	ECML PKDD 2020
其他作者:	Hutter, Frank.
團體作者:	ECML PKDD (Conference)
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xlii, 577 p. :ill., digital ;24 cm.
內容註:	Applied data science: recommendation -- applied data science: anomaly detection -- applied data science: Web mining -- applied data science: transportation -- applied data science: activity recognition -- applied data science: hardware and manufacturing -- applied data science: spatiotemporal data.
Contained By:	Springer Nature eBook
標題:	Machine learning - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-030-67670-4
ISBN:	9783030676704

Machine learning and knowledge discovery in databases = European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.. Part V /
Machine learning and knowledge discovery in databasesEuropean Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.Part V /[electronic resource] :ECML PKDD 2020edited by Frank Hutter ... [et al.]. - Cham :Springer International Publishing :2021. - xlii, 577 p. :ill., digital ;24 cm. - Lecture notes in computer science,124610302-9743 ;. - Lecture notes in computer science ;12461..

Applied data science: recommendation -- applied data science: anomaly detection -- applied data science: Web mining -- applied data science: transportation -- applied data science: activity recognition -- applied data science: hardware and manufacturing -- applied data science: spatiotemporal data.

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio-) temporal data and recurrent neural networks; collaborative filtering and matrix completion. Part II: deep learning optimization and theory; active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning. Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics. Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data. Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track.

ISBN: 9783030676704

Standard No.: 10.1007/978-3-030-67670-4doiSubjects--Topical Terms:

576368
Machine learning
--Congresses.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Machine learning and knowledge discovery in databases = European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.. Part V /
LDR:03556nmm a2200373 a 4500 001 2238054
003 DE-He213
005 20210224173421.0
006 m d
007 cr nn 008maaau
008 211111s2021 sz s 0 eng d
020 $a 9783030676704 $q (electronic bk.)
020 $a 9783030676698 $q (paper)
024 7 $a 10.1007/978-3-030-67670-4 $2 doi
035 $a 978-3-030-67670-4
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a UNF $2 bicssc
072 7 $a COM021030 $2 bisacsh
072 7 $a UNF $2 thema
072 7 $a UYQE $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .E19 2020
111 2 $a ECML PKDD (Conference) $d (2020 : $c Online) $3 3490826
245 1 0 $a Machine learning and knowledge discovery in databases $h [electronic resource] : $b European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings. $n Part V / $c edited by Frank Hutter ... [et al.].
246 3 $a ECML PKDD 2020
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xlii, 577 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 12461
490 1 $a Lecture notes in artificial intelligence
505 0 $a Applied data science: recommendation -- applied data science: anomaly detection -- applied data science: Web mining -- applied data science: transportation -- applied data science: activity recognition -- applied data science: hardware and manufacturing -- applied data science: spatiotemporal data.
520 $a The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio-) temporal data and recurrent neural networks; collaborative filtering and matrix completion. Part II: deep learning optimization and theory; active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning. Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics. Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data. Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track.
650 0 $a Machine learning $x Congresses. $3 576368
650 0 $a Data mining $v Congresses. $3 551626
650 1 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Computers and Education. $3 892757
650 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 892702
650 2 4 $a Computer Systems Organization and Communication Networks. $3 891212
700 1 $a Hutter, Frank. $3 3410298
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 12461. $3 3490831
830 0 $a Lecture notes in artificial intelligence. $3 3382562
856 4 0 $u https://doi.org/10.1007/978-3-030-67670-4
950 $a Computer Science (SpringerNature-11645)